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dc.creatorMolina Mora, José Arturo
dc.creatorChinchilla Montero, Diana
dc.creatorCastro Peña, Carolina
dc.creatorGarcía Santamaría, Fernando
dc.date.accessioned2022-03-03T20:25:05Z
dc.date.available2022-03-03T20:25:05Z
dc.date.issued2020
dc.identifier.citationhttps://journals.lww.com/md-journal/Fulltext/2020/12040/Two_dimensional_gel_electrophoresis__2D_GE__image.56.aspxes_ES
dc.identifier.issn0025-7974
dc.identifier.issn1536-5964
dc.identifier.urihttps://hdl.handle.net/10669/85945
dc.description.abstractTwo-dimensional gel electrophoresis (2D-GE) is an indispensable technique for the study of proteomes of biological systems, providing an assessment of changes in protein abundance under various experimental conditions. However, due to the complexity of 2D-GE gels, there is no systematic, automatic, and reproducible protocol for image analysis and specific implementations are required for each context. In addition, practically all available solutions are commercial, which implies high cost and little flexibility to modulate the parameters of the algorithms. Using the bacterial strain, Pseudomonas aeruginosaAG1 as a model, we obtained images from 2D-GE of periplasmic protein profiles when the strain was exposed to multiple conditions, including antibiotics. Then, we proceeded to implement and evaluate an image analysis protocol with open-source software, CellProfiler. First, a preprocessing step included a bUnwarpJ-Image pipeline for aligning 2D-GE images. Then, using CellProfiler, we standardized two pipelines for spots identification. Total spots recognition was achieved using segmentation by intensity, whose performance was evaluated when compared with a reference protocol. In a second pipeline with the same program, differential identification of spots was addressed when comparing pairs of protein profiles. Due to the characteristics of the programs used, our workflow can automatically analyze a large number of images and it is parallelizable, which is an advantage with respect to other implementations. Finally, we compared six experimental conditions of bacterial strain in the presence or absence of antibiotics, determining protein profiles relationships by applying clustering algorithms PCA (Principal Components Analysis) and HC (Hierarchical Clustering).es_ES
dc.description.sponsorshipUniversidad de Costa Rica/[803-B7-124]/UCR/Costa Ricaes_ES
dc.language.isoenges_ES
dc.sourceMedicine, vol.99(49), pp.e23373.es_ES
dc.subject2D-GEes_ES
dc.subjectBUnwarpJes_ES
dc.subjectCellProfileres_ES
dc.subjectImage analysises_ES
dc.subjectProteomicses_ES
dc.subjectPseudomonas aeruginosaes_ES
dc.titleTwo-dimensional gel electrophoresis (2D-GE) image analysis based on CellProfiler: Pseudomonas aeruginosa AG1 as modeles_ES
dc.typeartículo científicoes_ES
dc.identifier.doi10.1097/MD.0000000000023373
dc.description.procedenceUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Enfermedades Tropicales (CIET)es_ES
dc.identifier.codproyecto803-B7-124


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